Create a version of the MakeAppointment intent (from
the $LATEST version). In some cases, the console sends a request for
the update API operation before creating a new version.

Update the $LATEST version of the bot.

At this time, Amazon Lex builds a machine learning model for the bot.
When you test the bot in the console, the console uses the runtime
API to send user input back to Amazon Lex. Amazon Lex then uses the machine
learning model to interpret the user input.

The console shows the ScheduleAppointment bot. On the
Editor tab, review the preconfigured intent
(MakeAppointment) details.

Test the bot in the test window. Use the following screen shot to engage
in a test conversation with your bot:

Note the following:

From the initial user input ("Book an appointment"), the bot
infers the intent (MakeAppointment).

The bot then uses the configured prompts to get slot data from the
user.

The bot blueprint has the MakeAppointment intent
configured with the following confirmation prompt:

{Time} is available, should I go ahead and book your appointment?

After the user provides all of the slot data, Amazon Lex returns a
response to the client with a confirmation prompt as the message.
The client displays the message for the user:

16:00 is available, should I go ahead and book your appointment?

Notice that the bot accepts any appointment date and time values because
you don't have any code to initialize or validate the user data. In the next
section, you add a Lambda function to do this.